基于加权融合的多信源弹道数据实时野值检测方法

研究多信源弹道数据实时处理中斑点野值的检测问题.通过计算各信源数据的实时精度,给出了具有自适应加权系数的加权融合方法,实现了对目标状态参数较高精度的估计,从而实时、准确、高效地检测各信源数据野值.仿真结果表明,本方法可以快速、有效地检测多信源数据的斑点野值,解决因数据切换带来的台阶跳跃问题.

Real-time Outliers Detection in Multi-Source Trajectory Data Based on Weighted Fusion

This paper studies the detection of patchy outliers in real-time data processing for multi-source trajectory data. By calculating the accuracy of real-time data from each information source, we have proposed a weighted fusion method with adaptive weight, and have achieved the accurate estimation of target state parameters. And the method has accurately and efficiently fulfilled real-time outlier detection of the data from each information source. Simulations and applications show that the detection method proposed here can solve the problem of patchy detection efficiently and quickly. The method has also tackled the jump of the trajectory caused by shift of data from different tracking schemes of test range.